Trust Index based Model to Define News Credibility in Social Media Using Blockchain Technology

2020 ◽  
Vol 12 (SP7) ◽  
pp. 1622-1628
Author(s):  
Tee Wee Jing
Keyword(s):  
Social Media ◽  
Blockchain Technology ◽  
News Credibility

scholarly journals Social Trust-based Blockchain-enabled Social Media News Verification System

2021 ◽  
Vol 27 (9) ◽  
pp. 979-998
Author(s):  
Riri Fitri Sari ◽  
Asri Ilmananda ◽  
Daniela Romano
Keyword(s):  
Social Media ◽  
Social Trust ◽  
Fake News ◽  
Scale Free ◽  
Actual Truth ◽  
Blockchain Technology ◽  
Smart Contract ◽  
Verification System ◽  
News Credibility ◽  
Social Media Platforms

In the current digital era, information exchanges can be done easily through the Internet and social media. However, the actual truth of the news on social media platforms is hard to prove, and social media platforms are susceptible to the spreading of hoaxes. As a remedy, Blockchain technology can be used to ensure the reliability of shared information and can create a trusted communications environment. In this study, we propose a social media news spreading model by adapting an epidemic methodology and a scale-free network. A Blockchain-based news verification system is implemented to identify the credibility of the news and its sources. The effectiveness of the model is investigated by utilizing agent-based modelling using NetLogo software. In the simulations, fake news with a truth level of 20% are assigned a low News Credibility Indicator (NCI ± -0.637) value for all of the different network dimensions. Moreover, the Producer Reputation Credit is also decreased (PRC ± 0.213) so that the trust factor value is reduced. Our epidemic approach for news verification has also been implemented using Ethereum Smart Contract and several tools such as React with Solidity, IPFS, Web3.js, and Metamask. By showing the measurements of the credibility indicator and reputation credit to the user during the news dissemination process, this proposed smart contract can effectively limit user behaviour in spreading fake news and improve the content quality on social media.

Utilizing Blockchain Technology in Social Media Bot Identification

2020 ◽  
Author(s):  
Shreya Reddy ◽  
Lisa Ewen ◽  
Pankti Patel ◽  
Prerak Patel ◽  
Ankit Kundal ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Gold Standard ◽  
The Internet ◽  
Learning Models ◽  
Current Time ◽  
Machine Learning Methods ◽  
Blockchain Technology ◽  
Modern Age ◽  
Machine Learning Models

<p>As bots become more prevalent and smarter in the modern age of the internet, it becomes ever more important that they be identified and removed. Recent research has dictated that machine learning methods are accurate and the gold standard of bot identification on social media. Unfortunately, machine learning models do not come without their negative aspects such as lengthy training times, difficult feature selection, and overwhelming pre-processing tasks. To overcome these difficulties, we are proposing a blockchain framework for bot identification. At the current time, it is unknown how this method will perform, but it serves to prove the existence of an overwhelming gap of research under this area.<i></i></p>

Mitigating the consequences of negative news: How constructive journalism enhances self-efficacy and news credibility

Journalism ◽  
2021 ◽  
pp. 146488492110627
Author(s):  
Christian Staal Bruun Overgaard
Keyword(s):  
Social Media ◽  
Positive Affect ◽  
Self Efficacy ◽  
Positive Emotions ◽  
Mediating Role ◽  
Negative News ◽  
News Credibility ◽  
Broaden And Build Theory ◽  
Negative Feelings ◽  
Constructive Journalism

An informed electorate is vital for a well-functioning democracy. Yet many citizens intentionally avoid the news because it evokes negative feelings of disempowerment and distrust. This study ( n = 270) investigated how social media exposure to a new journalistic approach, constructive journalism, influences news consumers. The results showed that constructive social media posts, as compared to negative posts, led to higher levels of positive affect, self-efficacy, and perceived news credibility. In line with the broaden-and-build theory of positive emotions, the effects on self-efficacy and news credibility were mediated by positive affect. A similar mediating role was found for negative affect, counter to the theoretical expectations. These findings shed new light on the broaden-and-build theory, suggesting parts of it generalize to the context of news exposure on social media. The findings also suggest that constructive journalism may be an effective way to mitigate some of the main drivers of news avoidance in the 21st century.

Fake news on Facebook: examining the impact of heuristic cues on perceived credibility and sharing intention

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khudejah Ali ◽  
Cong Li ◽  
Khawaja Zain-ul-abdin ◽  
Muhammad Adeel Zaffar
Keyword(s):  
Public Health ◽  
Social Media ◽  
Design Methodology ◽  
Fake News ◽  
Content Type ◽  
Perceived Credibility ◽  
News Credibility ◽  
The Impact ◽  
Practical Implications ◽  
Active Processing

PurposeAs the epidemic of online fake news is causing major concerns in contexts such as politics and public health, the current study aimed to elucidate the effect of certain “heuristic cues,” or key contextual features, which may increase belief in the credibility and the subsequent sharing of online fake news.Design/methodology/approachThis study employed a 2 (news veracity: real vs fake) × 2 (social endorsements: low Facebook “likes” vs high Facebook “likes”) between-subjects experimental design (N = 239).FindingsThe analysis revealed that a high number of Facebook “likes” accompanying fake news increased the perceived credibility of the material compared to a low number of “likes.” In addition, the mediation results indicated that increased perceptions of news credibility may create a situation in which readers feel that it is necessary to cognitively elaborate on the information present in the news, and this active processing finally leads to sharing.Practical implicationsThe results from this study help explicate what drives increased belief and sharing of fake news and can aid in refining interventions aimed at combating fake news for both communities and organizations.Originality/valueThe current study expands upon existing literature, linking the use of social endorsements to perceived credibility of fake news and information, and sheds light on the causal mechanisms through which people make the decision to share news articles on social media.

Credibility Perceptions and Detection Accuracy of Fake News Headlines on Social Media: Effects of Truth-Bias and Endorsement Cues

2020 ◽  
pp. 009365022092132
Author(s):  
Mufan Luo ◽  
Jeffrey T. Hancock ◽  
David M. Markowitz
Keyword(s):  
Social Media ◽  
Deception Detection ◽  
Detection Accuracy ◽  
Fake News ◽  
Default Theory ◽  
Impact Detection ◽  
Truth Bias ◽  
News Credibility ◽  
Biased Processing ◽  
News Headlines

This article focuses on message credibility and detection accuracy of fake and real news as represented on social media. We developed a deception detection paradigm for news headlines and conducted two online experiments to examine the extent to which people (1) perceive news headlines as credible, and (2) accurately distinguish fake and real news across three general topics (i.e., politics, science, and health). Both studies revealed that people often judged news headlines as fake, suggesting a deception-bias for news in social media. Across studies, we observed an average detection accuracy of approximately 51%, a level consistent with most research using this deception detection paradigm with equal lie-truth base-rates. Study 2 evaluated the effects of endorsement cues in social media (e.g., Facebook likes) on message credibility and detection accuracy. Results showed that headlines associated with a high number of Facebook likes increased credibility, thereby enhancing detection accuracy for real news but undermining accuracy for fake news. These studies introduce truth-default theory to the context of news credibility and advance our understanding of how biased processing of news information can impact detection accuracy with social media endorsement cues.

scholarly journals NudgeCred: Supporting News Credibility Assessment on Social Media Through Nudges

2021 ◽  
Vol 5 (CSCW2) ◽  
pp. 1-30
Author(s):  
Md Momen Bhuiyan ◽  
Michael Horning ◽  
Sang Won Lee ◽  
Tanushree Mitra
Keyword(s):  
Social Media ◽  
Credibility Assessment ◽  
News Credibility

Diffusion of blockchain technology

2019 ◽  
Vol 32 (5) ◽  
pp. 735-757 ◽  
Author(s):  
Purva Grover ◽  
Arpan Kumar Kar ◽  
Marijn Janssen
Keyword(s):  
Social Media ◽  
Decision Process ◽  
Manufacturing Industry ◽  
Content Type ◽  
Academic Literature ◽  
Blockchain Technology ◽  
Data Source ◽  
Single Data ◽  
Almost All ◽  
Media Data

Purpose Although blockchain is often discussed, its actual diffusion seems to be varying for different industries. The purpose of this paper is to explore the blockchain technology diffusion in different industries through a combination of academic literature and social media (Twitter). Design/methodology/approach The insights derived from the academic literature and social media have been used to classify industries into five stages of the innovation-decision process, namely, knowledge, persuasion, decision, implementation and confirmation (Rogers, 1995). Findings Blockchain is found to be diffused in almost all industries, but the level of diffusion varies. The analysis highlights that manufacturing industry is at the knowledge stage. Further public administration is at persuasion stage. Subsequently, transportation, communications, electric, gas and sanitary services and trading industry had reached to the decision stage. Then, services industries have reached to implementation stage while finance, insurance and real estate industries are the innovators of blockchain technologies and have reached the confirmation stage of innovation-decision process. Practical implications Actual implementations of blockchain technology are still in its infancy stage for most of the industries. The findings suggest that specific industries are developing specific blockchain applications. Originality/value To the best of the authors’ knowledge this is the first study which is using social media data for investigating the diffusion of blockchain in industries. The results show that the combination of Twitter and academic literature analysis gives better insights into diffusion than a single data source.

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